Adrian Azoitei
MLOps Engineer at Enexis Group
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Adrian is a software engineer specialising in cloud-native systems, MLOps, data engineering, infrastructure, and observability. With experience at ASML and as a start-up co-founder, they combine strong technical expertise with a pragmatic, product-minded approach. They have also contributed to AI for Good projects, helping develop MLOps pipelines for wildlife monitoring and conservation. They focus on building reliable systems through clear architecture, automation, and effective collaboration.
Sovereign by Design: A Portable ML Platform for Tackling Energy Grid Congestion
Enexis is one of the EU’s most reliable energy grid operators, powering industry and millions of Dutch citizens. As grid congestion grows, Machine Learning becomes essential to strengthen our digital infrastructure and keep the grid reliable.
As these ML capabilities become critical to grid operations, the digital infrastructure supporting it must be as resilient and independent as the grid while being portable. Therefore, we cannot afford a single point of failure or entrust critical digital workloads to one provider. That is why we are pursuing a more portable and sovereign approach.
For utility companies greenfield environments are rare. We are therefore taking a staggered pragmatic approach, using Kubernetes, Kubeflow and Crossplane to build a solid foundation for the ML models that support our grid.
After this session, attendees will be able to understand how open-source software can support critical infrastructure and evaluate trade-offs in sovereignty and portability.
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